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https://issues.apache.org/jira/browse/HBASE-12394?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Weichen Ye updated HBASE-12394:
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Affects Version/s: (was: 0.98.6.1)
> Support multiple regions as input to each mapper in map/reduce jobs
> -------------------------------------------------------------------
>
> Key: HBASE-12394
> URL: https://issues.apache.org/jira/browse/HBASE-12394
> Project: HBase
> Issue Type: Improvement
> Components: mapreduce
> Affects Versions: 2.0.0
> Reporter: Weichen Ye
> Attachments: HBASE-12394-v2.patch, HBASE-12394-v3.patch,
> HBASE-12394-v4.patch, HBASE-12394-v5.patch, HBASE-12394-v6.patch,
> HBASE-12394.patch, HBase-12394 Document.pdf
>
>
> Welcome to the ReviewBoard :https://reviews.apache.org/r/27519/
> The Latest Patch is "Diff Revision 2 (Latest)"
> For Hadoop cluster, a job with large HBase table as input always consumes a
> large amount of computing resources. For example, we need to create a job
> with 1000 mappers to scan a table with 1000 regions. This patch is to support
> one mapper using multiple regions as input.
> In order to support multiple regions for one mapper, we need a new property
> in configuration--"hbase.mapreduce.scan.regionspermapper"
> hbase.mapreduce.scan.regionspermapper controls how many regions used as input
> for one mapper. For example,if we have an HBase table with 300 regions, and
> we set hbase.mapreduce.scan.regionspermapper = 3. Then we run a job to scan
> the table, the job will use only 300/3=100 mappers.
> In this way, we can control the number of mappers using the following formula.
> Number of Mappers = (Total region numbers) /
> hbase.mapreduce.scan.regionspermapper
> This is an example of the configuration.
> <property>
> <name>hbase.mapreduce.scan.regionspermapper</name>
> <value>3</value>
> </property>
> This is an example for Java code:
> TableMapReduceUtil.initTableMapperJob(tablename, scan, Map.class, Text.class,
> Text.class, job);
>
>
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